Radiological assessment of dementia: the Italian inter-society consensus for a practical and clinically oriented guide to image acquisition, evaluation, and reporting.

BACKGROUND: Radiological evaluation of dementia is expected to increase more and more in routine practice due to both the primary role of neuroimaging in the diagnostic pathway and the increasing incidence of the disease. Despite this, radiologists often do not follow a disease-oriented approach to image interpretation, for several reasons, leading to reports of limited value to clinicians. In our work, through an intersocietal consensus on the main mandatory knowledge about dementia, we proposed a disease-oriented protocol to optimize and standardize the acquisition/evaluation/interpretation and reporting of radiological images. Our main purpose is to provide a practical guideline for the radiologist to help increase the effectiveness of interdisciplinary dialogue and diagnostic accuracy in daily practice. RESULTS: We defined key clinical and imaging features of the dementias (A), recommended MRI protocol (B), proposed a disease-oriented imaging evaluation and interpretation (C) and report (D) with a glimpse to future avenues (E). The proposed radiological practice is to systematically evaluate and score atrophy, white matter changes, microbleeds, small vessel disease, consider the use of quantitative measures using commercial software tools critically, and adopt a structured disease-oriented report. In the expanding field of cognitive disorders, the only effective assessment approach is the standardized disease-oriented one, which includes a multidisciplinary integration of the clinical picture, MRI, CSF and blood biomarkers and nuclear medicine.

Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.

PURPOSE: Meningiomas are mainly benign tumors, though a considerable proportion shows aggressive behaviors histologically consistent with atypia/anaplasia. Histopathological grading is usually assessed through invasive procedures, which is not always feasible due to the inaccessibility of the lesion or to treatment contraindications. Therefore, we propose a multi-parametric MRI assessment as a predictor of meningioma histopathological grading. METHODS: Seventy-three patients with 74 histologically proven and previously treated meningiomas were retrospectively enrolled (42 WHO I, 24 WHO II, 8 WHO III) and studied with MRI including T2 TSE, FLAIR, Gradient Echo, DWI, and pre- and post-contrast T1 sequences. Lesion masks were segmented on post-contrast T1 sequences and rigidly registered to ADC maps to extract quantitative parameters from conventional DWI and intravoxel incoherent motion model assessing tumor perfusion. Two expert neuroradiologists assessed morphological features of meningiomas with semi-quantitative scores. RESULTS: Univariate analysis showed different distributions (p < 0.05) of quantitative diffusion parameters (Wilcoxon rank-sum test) and morphological features (Pearson's chi-square; Fisher's exact test) among meningiomas grouped in low-grade (WHO I) and higher grade forms (WHO II/III); the only exception consisted of the tumor-brain interface. A multivariate logistic regression, combining all parameters showing statistical significance in the univariate analysis, allowed discrimination between the groups of meningiomas with high sensitivity (0.968) and specificity (0.925). Heterogeneous contrast enhancement and low ADC were the best independent predictors of atypia and anaplasia. CONCLUSION: Our multi-parametric MRI assessment showed high sensitivity and specificity in predicting histological grading of meningiomas. Such an assessment may be clinically useful in characterizing lesions without histological diagnosis. Key points • When surgery and biopsy are not feasible, parameters obtained from both conventional and diffusion-weighted MRI can predict atypia and anaplasia in meningiomas with high sensitivity and specificity. • Low ADC values and heterogeneous contrast enhancement are the best predictors of higher grade meningioma.